We report a novel approach to the measurement of colored tablet coating thickness, which employs Raman spectroscopy with univariate and multivariate data analysis. Our results suggest that Raman sensing can serve as a viable non-invasive means to quantify tablet coating thickness in the presence of a fluorescent ingredient in the coating formulation (food colorant Alphazurine FG or D&C Blue No. 4). This study comparatively tests the advantage of several data transformation approaches, including mean centering, standard normal variate, and Savitzky-Golay smoothed second derivative as means of improving predictive models in the presence of fluorescence. By application of the partial least squares (PLS) calibration algorithm to establish optimum covariance between transformed spectral data and measured tablet coating thicknesses, we have been able to create predictive models with calibration errors as small as 4 mu m for a training set that spans colored coating thicknesses from 50 to 151 mu m. (c) 2006 Elsevier B.V. All rights reserved.